Insights into Missense SNPs on Amyloidogenic Proteins

<b>Background:</b> Amyloidogenic proteins, a heterogenous group of proteins characterized by their ability to form amyloid fibrils, lead to pathological conditions when they undergo abnormal folding and self-assembly. Missense single-nucleotide polymorphisms (msSNPs) may occur in their sequence, disrupting the normal structure and function of these proteins, pushing them towards amyloidogenesis. <b>Methods:</b> A comprehensive dataset of amyloidogenic proteins was created and their msSNPs were collected and mapped on their amino acid sequence. The chi squared test, logistic regression and the bootstrap method were used to ascertain the statistical significance of the results. <b>Results:</b> The distribution of pathogenic and benign msSNPs highlighted the predicted amyloidogenic segments as hotspots for pathogenic msSNPs. Analysis of the change in residue properties and pathogenicity status revealed that the substitution of negatively charged residues by any other type of residue tends to be pathogenic. Furthermore, certain substitutions were found to be more likely pathogenic than average. Additionally, a case study of APP, a key protein in Alzheimer's disease, is used as an example. <b>Conclusions:</b> This study will hopefully showcase the importance of amyloidogenic protein msSNPs as well as spark an interest in research of the mechanisms that lead to the formation of amyloid deposits under the scope of pathogenic msSNPs.

Institutions

Publication Details

Journal
Proteomes
Published
2025-12-02
DOI
https://doi.org/10.3390/proteomes13040064
Primary Topic
Alzheimer's disease research and treatments
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Insights into Missense SNPs on Amyloidogenic Proteins

Proteomes
Alzheimer's disease research and treatments
article

Insights into Missense SNPs on Amyloidogenic Proteins

article en

Abstract

<b>Background:</b> Amyloidogenic proteins, a heterogenous group of proteins characterized by their ability to form amyloid fibrils, lead to pathological conditions when they undergo abnormal folding and self-assembly. Missense single-nucleotide polymorphisms (msSNPs) may occur in their sequence, disrupting the normal structure and function of these proteins, pushing them towards amyloidogenesis. <b>Methods:</b> A comprehensive dataset of amyloidogenic proteins was created and their msSNPs were collected and mapped on their amino acid sequence. The chi squared test, logistic regression and the bootstrap method were used to ascertain the statistical significance of the results. <b>Results:</b> The distribution of pathogenic and benign msSNPs highlighted the predicted amyloidogenic segments as hotspots for pathogenic msSNPs. Analysis of the change in residue properties and pathogenicity status revealed that the substitution of negatively charged residues by any other type of residue tends to be pathogenic. Furthermore, certain substitutions were found to be more likely pathogenic than average. Additionally, a case study of APP, a key protein in Alzheimer's disease, is used as an example. <b>Conclusions:</b> This study will hopefully showcase the importance of amyloidogenic protein msSNPs as well as spark an interest in research of the mechanisms that lead to the formation of amyloid deposits under the scope of pathogenic msSNPs.

ProteomesVol. 13(4)
National and Kapodistrian University of Athens (GR)
European Commission, European Social Fund
Openalex Percentile: Top 38%
Alzheimer's disease research and treatments
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.